The State of AI Language Translation & What The Future Holds
Artificial intelligence (AI) continuously wows or terrifies us, but there’s no denying that AI will play an essential role in human development over the next decade. Machine translation, which has been around since the 1950s, will soon make extreme strides thanks to AI technologies.
The Current State of AI-Language Translation
AI language translation is rooted in machine translation, which is a specialized technology that translates text without human assistance. While machine translation did come first, artificial intelligence translation and technology were developed side-by-side and aided their progress.
That means that speech-to-text and the software that supports it have a symbiotic relationship. Both use neural networks and AI machines to mimic human intelligence, and that’s remained true since the technology’s inception. Unfortunately, lack of support and funding has caused several delays in the development of sophisticated AI language translation technology.
Stakeholders are more interested in technology that reduces business overheads, and artificial intelligence language translation isn’t to the point where it can completely replace human labor.
But based on this Lokalise vs. Smartling review by Weglot, AI translation software can already:
- Translate an entire website in minutes. Faster translations can save companies a lot of money on labor and allows them to reach an audience they otherwise wouldn’t have.
- Use neural machine translation (NLP) to provide accurate translations. Artificial intelligence translation software often has issues with context, but NLP solves this problem because it’s constantly learning, growing, and perfecting its programming.
- Translate English into 100 (or more) languages. While AI translation software can’t translate lesser-known languages, it can translate the most popular languages.
Data scientists are continuing to engineer new breakthroughs in language technology, so we’re likely going to see an AI renaissance in the next decade, provided we have the funding.
Translation Technology and Human Translators
All AI topics typically come with baggage. After all, AI is designed to replace human labor, which inevitably makes us hostile toward computers. It’s estimated that 40% of the human workforce will be replaced by AI, so where does that leave human translators? Will they still be employed?
The answer is “yes” unless we’re able to perfectly mimic human behavior, which is impossible with our current knowledge of AI and computers. Neural translations are close to mimicking actual human speech, but NLP can sometimes input language data seemingly out of nowhere.
There’s also the issue with culture. Speech changes so fast that computers may not be able to keep up. In the end, a human has to review each translation to ensure it makes logical sense.
The Future of AI-Language Translation Technology
If AI language technology won’t replace humans entirely, then what will it look like in the future?
No matter what AI translation breakthroughs occur in the future, the purpose of the technology will remain the same: enhancing the performance of human translators. Currently, we can use machine translation tools to instantly translate text, which can serve as a basic first draft.
This already reduces a translator’s workload significantly, which leads us to believe it will reduce further in the future. That’s because AI translation software will eventually be able to translate dialog effortlessly in real-time. For now, translating real-time speech is still a messy endeavor.
We assume the future of AI language translation technology will include:
- Faster data analysis and real-time online document updates
- Overcoming communication barriers in over 6,000 languages
- Perfected voice translation and speech-to-text translation
While this doesn’t look like much, the goal of future language technology developments will mostly rely on perfecting the software that’s already in place. Globalization will likely make it easier for data scientists to increase their funding, which will help move the technology along.
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